Model Routing
Policy-driven selection across self-hosted and brokered models by cost, latency, capability, and compliance requirements.
Strategic Focus · 01
AI Model-as-a-Service
One platform, two sources of intelligence. We operate a self-built compute resource pool serving leading open-source models, and we aggregate closed-source models into the same pool as brokered APIs — so customers reach every capability through a single, governed, metered interface.
Platform Architecture
Two pillars, unified into one resource pool.
Pillar A — Self-Built Compute
Our own GPU resource pool, serving open-source models
We build and operate dedicated GPU compute capacity and curate leading open-source foundation models — spanning language, vision, and multimodal families — into a managed serving layer that we control end to end.
- Curated catalogue of leading open-weight models, versioned and maintained by our engineering team
- Dedicated and shared GPU capacity options for predictable latency and throughput
- Data residency under customer control — workloads run inside our operated infrastructure
- Fine-tuning and adaptation services for domain-specific deployment
Pillar B — Model Aggregation
Closed-source models, brokered as managed APIs
We integrate leading proprietary models into the same resource pool as API services — operating as an authorised access layer and relay point so customers consume premium model capabilities without managing multiple vendor relationships.
- Unified API gateway with a consistent interface across heterogeneous model providers
- Intelligent routing, failover, and load balancing across available models
- Consolidated metering, quota management, and a single commercial relationship
- Access governance: authentication, rate policy, and audit logging on every call
The Unified Layer
One interface. Every model. Full accountability.
The two pillars are not separate products — they are one platform. A single API endpoint dispatches each request to the most appropriate model, whether it runs on our own GPUs or on a partner's infrastructure. Customers see one contract, one bill, one service level, and one point of operational responsibility.
Metering & Governance
Per-workload usage metering, spending controls, and complete audit trails suitable for regulated environments.
Solution Engineering
Reference architectures and integration support that turn raw model access into production business applications.
Automotive Intelligence
Assisted-driving compute, served from our own pool.
Our EV solutions practice works directly with vehicle manufacturers on charging infrastructure and energy systems. Those relationships give us a practical understanding of where automotive AI is heading — and where its compute bottlenecks sit.
Building on that foundation, we offer automotive partners a dedicated path for the compute-intensive work behind assisted driving: perception model training and evaluation, scenario simulation, sensor-data processing, and continuous model iteration. These workloads run inside our MaaS resource pool, under governance terms defined with each partner.
The result is a closed loop that few providers can offer: infrastructure at the roadside, and infrastructure behind the intelligence that drives on it.
Engineering Depth
Grounded in applied research.
Our engineering team stays engaged with the research community in areas adjacent to model serving — including efficient inference, resource scheduling, and energy-aware computing — and has contributed to peer-reviewed publications and technical presentations at international venues in these fields.
We treat this engagement as an input to platform quality: the scheduling, metering, and efficiency techniques in our resource pool reflect current applied research, translated into production practice.
Engagement Models
How organisations consume the platform.
API Consumption
Metered, pay-per-use access to the full model catalogue through the unified gateway — the fastest path from evaluation to production.
Reserved Capacity
Committed GPU allocations within our self-built pool for workloads that demand guaranteed throughput, isolation, or data-residency terms.
Managed Solutions
End-to-end delivery of model-powered applications — from model selection and adaptation to integration, operations, and ongoing optimisation.